气流 - EMR操作员中的任务实例

Question

在Airflow中，我面临的问题是我需要将job_flow_id传递给我的一个emr-steps。我能够从运营商检索job_flow_id但是当我要创建提交到集群的步骤时，task_instance值不正确。我有以下代码：

def issue_step(name, args):
    return [
        {
            "Name": name,
            "ActionOnFailure": "CONTINUE",
            "HadoopJarStep": {
                "Jar": "s3://....",
                "Args": args
            }
        }
    ]

dag = DAG('example',
          description='My dag',
          schedule_interval='0 8 * * 6',
          dagrun_timeout=timedelta(days=2))

try:

    create_emr = EmrCreateJobFlowOperator(
        task_id='create_job_flow',
        aws_conn_id='aws_default',        
        dag=dag
    )

    load_data_steps = issue_step('load', ['arg1', 'arg2'])

    load_data_steps[0]["HadoopJarStep"]["Args"].append('--cluster-id')
    load_data_steps[0]["HadoopJarStep"]["Args"].append(
        "{{ task_instance.xcom_pull('create_job_flow', key='return_value') }}") # the value here is not exchanged with the actual job_flow_id

    load_data = EmrAddStepsOperator(
        task_id='load_data',
        job_flow_id="{{ task_instance.xcom_pull('create_job_flow', key='return_value') }}",  # this is correctly exchanged with the job_flow_id - same for the others
        aws_conn_id='aws_default',
        steps=load_data_steps,
        dag=dag
    )

    check_load_data = EmrStepSensor(
        task_id='watch_load_data',
        job_flow_id="{{ task_instance.xcom_pull('create_job_flow', key='return_value') }}",
        step_id="{{ task_instance.xcom_pull('load_data', key='return_value')[0] }}",
        aws_conn_id='aws_default',
        dag=dag
    )

    cluster_remover = EmrTerminateJobFlowOperator(
        task_id='remove_cluster',
        job_flow_id="{{ task_instance.xcom_pull('create_job_flow', key='return_value') }}",
        aws_conn_id='aws_default',
        dag=dag
    )

    create_emr_recommendations >> load_data
    load_data >> check_load_data
    check_load_data >> cluster_remover

except AirflowException as ae:
    print ae.message

问题是，当我检查EMR时，而不是在--cluster-id j-1234步骤中看到load_data，我看到--cluster-id "{{task_instance.xcom_pull('create_job_flow', key='return_value')}}"，这导致我的步骤失败。

如何在步进功能中获得实际值？

谢谢，节日快乐

Answer 1

我发现气流库中有关于this的PR。问题是EmrAddStepsOperator没有模板化步骤。为了解决这个问题，我做了以下事情：

• 创建了一个继承自EmrAddStepsOperator的自定义运算符
• 添加此运算符作为插件
• 在我的DAG文件中调用新运算符

这里是自定义运算符的代码和文件custom_emr_add_step_operator.py中的插件（参见下面的树）

from __future__ import division, absolute_import, print_function

from airflow.plugins_manager import AirflowPlugin
from airflow.utils import apply_defaults

from airflow.contrib.operators.emr_add_steps_operator import EmrAddStepsOperator


class CustomEmrAddStepsOperator(EmrAddStepsOperator):
    template_fields = ['job_flow_id', 'steps'] # override with steps to solve the issue above

    @apply_defaults
    def __init__(
            self,
            *args, **kwargs):
        super(CustomEmrAddStepsOperator, self).__init__(*args, **kwargs)

    def execute(self, context):
        super(CustomEmrAddStepsOperator, self).execute(context=context)


# Defining the plugin class
class CustomPlugin(AirflowPlugin):
    name = "custom_plugin"
    operators = [CustomEmrAddStepsOperator]

在我的DAG文件中，我以这种方式调用了插件

from airflow.operators import CustomEmrAddStepsOperator

我的项目和插件的结构如下所示：

├── config
│   └── airflow.cfg
├── dags
│   ├── __init__.py
│   └── my_dag.py
├── plugins
│   ├── __init__.py
│   └── operators
│       ├── __init__.py
│       └── custom_emr_add_step_operator.py
└── requirements.txt

如果您使用的是像PyCharm这样的IDE，这会引发抱怨，因为它说无法找到模块。但是当您运行Airflow时，不会出现此问题。还要记住确保在你的airflow.cfg中你要指向正确的plugins文件夹，以便Airflow能够读取你新创建的插件。